Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-2, 4, 6-7, 9 and 11-14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chou et al. (U.S. 2017/0347120), hereinafter Chou in view of WG7, MPEG 3D Graphics Coding, "G-PCC codec description," INTERNATIONAL ORGANIZATION FOR STANDARDIZATION ORGANISATION INTERNATIONALE DE NORMALISATION ISO/IEC JTC 1/SC 29/WG 7 MPEG 3D GRAPHICS CODING ISO/IEC JTC 1/SC 29/WG 7 N0011, October 2020, hereinafter G-PCC. G-PCC was cited in the Applicant’s IDS dated 12/26/23 with a copy used by the Examiner for citations attached to the current office action.
Regarding claims 1 and 6, Chou discloses a device for encoding point cloud data, the device comprising:
a geometry encoder (Chou [0059], [0192] and figs. 19a-19b) configured to encode geometry data in the point cloud data (Chou [0005]);
an attribute encoder (Chou [0060], [0192] and figs. 19a-19b) configured to encode attribute data in the point cloud data based on the geometry data (Chou [0053] and [0075]-[0076]); and
a transmitter (Chou [0192]) and figs. 19a-19b) configured to transmit the encoded geometry data, the encoded attribute data, and signaling information (Chou [0177]-[0178], figs. 4, 18a-18b and 19a),
wherein the geometry encoder (Chou [0059], [0192] and figs. 19a-19b) compresses the geometry data based on an inter-frame prediction (Chou [0065], [0112], [0178] and Abstract) and an octree (Chou [0081], [0112] and figs. 19a-19b),
wherein the compression of an occupancy tree node in the octree depends on neighbor occupancy patterns for the occupancy tree node (Chou [0126] and fig. 5).
Chou does not explicitly disclose wherein a number of the neighbor occupancy patterns is reduced by applying at least rotations or reflections.
However, G-PCC teaches wherein the compression of an occupancy tree node in the octree depends on neighbor occupancy patterns for the occupancy tree node (G-PCC pgs. 13-14, section 3.2.2.1), and
wherein a number of the neighbor occupancy patterns is reduced by applying at least rotations or reflections (G-PCC p. 14, fig. 6 and accompanying description).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Chou’s device with the missing limitations as taught by G-PCC to achieve optimal compression performance and avoid dilution of occupancy statistics into too many states (G-PCC p. 4, top).
Regarding claims 2 and 7, Chou in view of G-PCC teaches the method and device of claims 1 and 6, wherein the geometry encoder comprises:
a motion estimator (Chou [0057] and fig. 19b) configured to estimate a motion vector by performing motion estimation within a search window of a reference frame (Chou [0122], [0126] and fig. 5);
a motion compensator (Chou [0064] and fig. 19b) configured to perform motion compensation based on the estimated motion vector and select a predictor in the reference frame as a set of nodes having similar characteristics to a prediction unit in a current frame, wherein the prediction unit is a set of neighbor nodes at a specific depth of the octree in the current frame (Chou [0124]-[0126], [0178], [0112] and fig. 5);
a neighbor occupancy pattern generator (Chou [0192]) configured to compare a neighbor occupancy pattern of the prediction unit with a neighbor occupancy pattern of the predictor (Chou [0125]-[0126]); and
an entropy encoder (Chou [0057] and figs. 19a-19b) configured to entropy code residual information related to the geometry data based on a result of the comparison (Chou [0064] and figs. 19a-19b).
Regarding claims 4 and 9, Chou in view of G-PCC teaches the method and device of claims 2 and 7, wherein the neighbor occupancy pattern generator is configured to:
generate the neighbor occupancy pattern of the prediction unit based on occupancy information about at least one neighbor node of a compression target node of the prediction unit (Chou [0124]-[0126] and fig. 5); and
generate the neighbor occupancy pattern of the predictor based on occupancy information about at least one neighbor node of the predictive node of the predictor (Chou [0124]-0126] and fig. 5).
Regarding claim 11, Chou in view of G-PCC teaches a method of decoding point cloud data, the method comprising:
receiving geometry data, attribute data, and signaling information (Chou [0075] and figs. 20a-20b);
decoding the geometry data based on the signaling information (Chou [0075]-[0076] and figs. 20a-20b); and
decoding the attribute data based on the signaling information and the decoded geometry data (Chou [0075] and fig. 20a-20b);
wherein the decoding of the geometry data comprises:
decoding the geometry data based on an inter-frame prediction (Chou [0065], [0112], [0178] and Abstract) and an octree (Chou [0081], [0112] and figs. 20a-20b),
wherein the decoding of an occupancy tree node in the octree depends on neighbor occupancy patterns for the occupancy tree node (Chou [0126] and fig. 5 and G-PCC pgs. 13-14, section 3.2.2.1), and
wherein a number of the neighbor occupancy patterns is reduced by applying at least rotations or reflections (G-PCC p. 14, fig. 6 and accompanying description) (claim 11 recites analogous limitations to claim 1 above, and is therefore rejected on the same premise. Furthermore, claim 11 discloses an inverse of encoding and Chou discloses both encoding and decoding methods (Chou Abstract, figs. 19a-19b and 20a-20b)).
Regarding claim 12, Chou in view of G-PCC teaches the method of claim 11, wherein the decoding of the geometry data comprises:
generating the octree based on motion vector information included in the signaling information (Chou [0124]-[0126], [0178], [0112], [0075] and fig. 5);
generating a neighbor occupancy pattern of a prediction unit in the current frame based on the octree (Chou [0125]-[0126] and [0112]);
performing motion compensation based on the motion vector information and selecting a predictor in the reference frame as a set of nodes having similar characteristics to the prediction unit in the current frame, wherein the prediction unit is a set of neighbor nodes at a specific depth of the octree in the current frame (Chou [0124]-[0126], [0178], [0112] and fig. 5);
generating a neighbor occupancy pattern of the predictor (Chou [0125]-[0126]);
comparing the neighbor occupancy pattern of the prediction unit with the neighbor occupancy pattern of the predictor (Chou [0125]-[0126]); and
entropy decoding residual information related to the geometry data based on a result of the comparison (Chou [0064] and figs. 20a-20b) (claim 12 recites analogous limitations to claim 2 above, and is therefore rejected on the same premise. Furthermore, claim 12 discloses an inverse of encoding and Chou discloses both encoding and decoding methods (Chou Abstract, figs. 19a-19b and 20a-20b)).
Regarding claim 13, Chou in view of G-PCC teaches the method of claim 12, wherein the neighbor occupancy pattern of the prediction unit is generated based on occupancy information about at least one neighbor node of a node to be reconstructed in the prediction unit (Chou [0124]-[0126] and fig. 5),
wherein the neighbor occupancy pattern of the predictor is generated based on the occupancy information about at least one neighbor node of the predictive node of the predictor (Chou [0124]-0126] and fig. 5) (claim 13 recites analogous limitations to claim 4 above, and is therefore rejected on the same premise. Furthermore, claim 13 discloses an inverse of encoding and Chou discloses both encoding and decoding methods (Chou Abstract, figs. 19a-19b and 20a-20b)).
Regarding claim 14, Chou in view of G-PCC teaches the method of claim 12, wherein the comparing comprises:
determining a similarity between a node to be reconstructed in the current frame and a predictive node in the reference frame by comparing the neighbor occupancy pattern of the prediction unit with the neighbor occupancy pattern of the predictor (Chou [0124]-[0126], [0178], [0112] and fig. 5) (claim 14 recites analogous limitations to claim 2 above, and is therefore rejected on the same premise. Furthermore, claim 14 discloses an inverse of encoding and Chou discloses both encoding and decoding methods (Chou Abstract, figs. 19a-19b and 20a-20b)).
Regarding claim 16, Chou in view of G-PCC teaches a device for decoding point cloud data, the device comprising:
a receiver (Chou [0077], [0192] and figs. 20a-20b) to receive geometry data, attribute data, and signaling information;
a geometry decoder (Chou [0075], [0192] and figs. 20a-20b) to decode the geometry data based on the signaling information; and
an attribute decoder (Chou [0075], [0192] and figs. 20a-20b) to decode the attribute data based on the signaling information and the decoded geometry data,
wherein the geometry decoder performs decoding of the geometry data based on an inter- frame prediction and an octree,
wherein the decoding of an occupancy tree node in the octree depends on neighbor occupancy patterns for the occupancy tree node, and
wherein a number of the neighbor occupancy patterns is reduced by applying at least rotations or reflections (see claim 11 for remaining limitations as claim 16 is analogous to claim 11).
Claim(s) 3 and 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chou in view of G-PCC as applied to claims 2 and 7 above, and further in view of Lasserre et al (U.S. 2020/0258262), hereinafter Lasserre.
Regarding claims 3 and 8, Chou in view of G-PCC teaches the method and device of claims 2 and 7, wherein the motion estimator is configured to:
generate a residual (Chou [0101]) based on a compression target node of the prediction unit, at least one neighbor node of the compression target node, a predictive node of the predictor, and at least one neighbor node of the predictive node (Chou [0124]-[0126] and fig. 5); and
estimate the motion vector based on the prediction error (Chou [0124]).
Chou does not explicitly disclose that residual is prediction error.
However, Lasserre teaches residual is prediction error (Lasserre [0061]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the device taught by Chou in view of G-PCC with the missing limitations as taught by Lasserre to exploit temporal redundancy between neighboring frames (Lasserre [0061]).
Claim(s) 5, 10 and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chou in view of G-PCC as applied to claims 2 and 7 above, and further in view of Zhang et al (U.S. 2021/0042989), hereinafter Zhang.
Regarding claims 5 and 10, Chou in view of G-PCC teaches the method and device of claims 2 and 7, wherein the signaling information comprises geometry compression related information (Chou [0177]-[0178]),
wherein the geometry compression related information comprises at least motion vector information (Chou [0178]), reference frame information (Chou [0137])
Chou does not explicitly disclose range information related to a depth of the octree for transmission of the motion vector.
However, Zhang teaches range information related to a depth of the octree for transmission of the motion vector (Zhang [0028]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the device taught by Chou in view of G-PCC with the missing limitations as taught by Zhang to enable a geometry model for a specified range (Zhang [0028]).
Regarding claim 15, Chou in view of G-PCC and further in view of Zhang teaches the method of claim 12, wherein the signaling information comprises geometry compression related information,
wherein the geometry compression related information comprises at least the motion vector information, reference frame information, and range information related to a depth of the octree for transmission of the motion vector (claim 15 recites analogous limitations to claim 5 above, and is therefore rejected on the same premise. Furthermore, claim 15 discloses an inverse of encoding and Chou discloses both encoding and decoding methods (Chou Abstract, figs. 19a-19b and 20a-20b)).
The same motivation and analysis for claim 5 applies to claim 15.
Response to Arguments
Applicant's arguments filed in regard to the newly amended claims have been fully considered but are moot because the arguments do not apply to the current grounds of rejection being used in the current rejection, i.e. G-PCC.
Under the broadest reasonable interpretation of the current claim language “occupancy tree node” and “neighbor occupancy patterns”, Chou at least discloses compressing an occupancy tree node depending on neighbor occupancy patterns (Chou [0126] and fig. 5). Moreover, G-PCC teaches the amendment (G-PCC p. 14, fig. 6) and uses the same figure to describe the Applicant’s amendment as the Applicant’s Specification (fig. 21). Further, see additional prior art Sugio found below for the amended subject matter after further search and consideration of the amended claims. Therefore, the combination of the Chou and G-PCC teaches the amended limitations.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Sugio et al. (U.S. 2021/0099697) teaching a reduction in a number of neighbor occupancy patterns by rotation ([0786] and [0790]).
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/MATTHEW K KWAN/Primary Examiner, Art Unit 2482
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